Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis N Gaggion, L Mansilla, C Mosquera, DH Milone, E Ferrante IEEE Transactions on Medical Imaging 42 (2), 546-556, 2022 | 45 | 2022 |
Chest x-ray automated triage: A semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning … C Mosquera, FN Diaz, F Binder, JM Rabellino, SE Benitez, AD Beresñak, ... Computer Methods and Programs in Biomedicine 206, 106130, 2021 | 14 | 2021 |
Towards unraveling calibration biases in medical image analysis MA Ricci Lara, C Mosquera, E Ferrante, R Echeveste Workshop on Clinical Image-Based Procedures, 132-141, 2023 | 10 | 2023 |
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images N Gaggion, C Mosquera, L Mansilla, JM Saidman, M Aineseder, ... Scientific Data 11 (1), 511, 2024 | 7 | 2024 |
User satisfaction with an AI system for chest X-Ray analysis implemented in a hospital’s emergency setting D Rabinovich, C Mosquera, P Torrens, M Aineseder, S Benitez Challenges of Trustable AI and Added-Value on Health, 8-12, 2022 | 7 | 2022 |
Impact of class imbalance on chest x-ray classifiers: towards better evaluation practices for discrimination and calibration performance C Mosquera, L Ferrer, D Milone, D Luna, E Ferrante arXiv preprint arXiv:2112.12843, 2021 | 6 | 2021 |
Integration of a deep learning system for automated chest x-ray interpretation in the emergency department: A proof-of-concept C Mosquera, F Binder, FN Diaz, A Seehaus, G Ducrey, JA Ocantos, ... Intelligence-Based Medicine 5, 100039, 2021 | 5 | 2021 |
Class imbalance on medical image classification: Towards better evaluation practices for discrimination and calibration performance C Mosquera, L Ferrer, DH Milone, D Luna, E Ferrante European Radiology 34 (12), 7895-7903, 2024 | 4 | 2024 |
Introducing Computer Vision into Healthcare Workflows C Mosquera, MAR Lara, FN Díaz, F Binder, SE Benitez Digital Health: From Assumptions to Implementations, 43-62, 2023 | 3 | 2023 |
Measuring the delay in the referral of unstable vertebral metastasis to the spine surgeon: a retrospective study in a Latin American institution F Landriel, FP Lichtenberger, L Ulloque-Caamaño, C Mosquera, ... Neurology India 71 (5), 902-906, 2023 | 2 | 2023 |
Three-dimensional printing and navigation in bone tumor resection LE Ritacco, C Mosquera, I Albergo, DL Muscolo, GL Farfalli, MA Ayerza, ... 3D Printing, 2018 | 1 | 2018 |
Artificial Intelligence Assistance for the Measurement of Full Alignment Parameters in Whole-Spine Lateral Radiographs F Landriel, BC Franchi, C Mosquera, FP Lichtenberger, S Benitez, ... World Neurosurgery, 2024 | | 2024 |
Towards unraveling calibration biases in medical image analysis M Agustina Ricci Lara, C Mosquera, E Ferrante, R Echeveste arXiv e-prints, arXiv: 2305.05101, 2023 | | 2023 |
39P OLIMPIA dataset: Radiomics to predict outcomes in EGFR-mutant non-small cell lung cancer G Pérez, JN Minatta, M Aineseder, C Mosquera, SE Benitez Annals of Oncology 33, S18, 2022 | | 2022 |
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis RN Gaggion Zulpo, LA Mansilla, C Mosquera, DH Milone, E Ferrante Institute of Electrical and Electronics Engineers, 2022 | | 2022 |
P60. 05 Radiomic Signature to Predict Outcomes in EGFR-Mutant Non-Small Cell Lung Cancer JN Minatta, D Deza, M Aineseder, MM Nuñez, C Mosquera, L Lupinacci, ... Journal of Thoracic Oncology 16 (10), S1166, 2021 | | 2021 |
1174P Preliminary prediction of EGFR-mutant non-small cell lung cancer outcome using radiomic signature JN Minatta, C Mosquera, M Aineseder, MAM Nuñez, D Deza, L Lupinacci, ... Annals of Oncology 32, S941-S942, 2021 | | 2021 |
Understanding the impact of class imbalance on the performance of chest x-ray image classifiers. C Mosquera, L Ferrer, DH Milone, DR Luna, E Ferrante CoRR, 2021 | | 2021 |
Chest x-ray automated triage: a semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning … C Mosquera, FN Diaz, F Binder, JM Rabellino, SE Benitez, AD Beresñak, ... arXiv preprint arXiv:2012.12712, 2020 | | 2020 |
FOUR DEEP LEARNING ARCHITECTURES. C Mosquera, F Diaz, F Binder, JM Rabellino, SE Benitez, A Beresñak, ... arXiv preprint arXiv:2012.12712, 2020 | | 2020 |